Performance Analysis on RIS-Aided Wideband Massive MIMO OFDM Systems with Low-Resolution ADCs

In this paper, we derive the achievable rate of single-carrier frequency domain equalizer (SC-FDE) and orthogonal frequency division multiplexing (OFDM) systems, constrained on low resolution analog to digital converters (ADCs). We assume that there is a full knowledge of channels at both transmitter and receiver sides. We model low resolution ADCs with an additive uniform quantization noise. We consider an ultra-wide band millimeter wave (mm-Wave) system with a frequency selective channel. The channel is based on practical results at mm-Wave frequencies. Our numerical results show that SC-FDE systems with minimum mean square error (MMSE) equalizers outperform OFDM and SC-FDE systems with zero forcing (ZF) equalizers at high signal to noise ratio (SNR) regimes. Moreover, benefits of increasing the ADCs resolution are not significant due to exponentially increment in the power consumption of ADCs.

In this paper, we analyze the Bit Error Rate (BER) performance of Golden coded Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system over Rician multipath fading channel. We also compare the performance of the MIMO-OFDM system using Golden code in Rayleigh and Rician multipath fading channels. We discuss the effects of the presence of line-of-sight (LoS) component in the multipath fading environment which renders the improvement in the overall performance of the Golden coded MIMO-OFDM. This paper discusses the performance of Golden codes in a frequency selective Rician fading channel. To deal with the frequency selective fading channel, we use the OFDM (Orthogonal Frequency Division Multiplexing) modulation. The BER performance of the Golden coded MIMO-OFDM system under several propagation conditions has been evaluated. Keywords—MIMO, OFDM, Golden STBC, Rayleigh fading, Rician fading.

Millimeter wave communications are sensitive to complex scattering environments (e.g., to the presence of obstacles), which can be mitigated by reconfigurable intelligent surfaces (RISs). Traditional nearly passive RISs lack the ability to perform signal processing operations, which makes channel estimation in RIS-aided communications more challenging. Hence, in this paper, we focus on a hybrid RIS architecture, which is equipped with a small number of active elements. These active elements can be connected with baseband processing units through radio frequency (RF) chains. We estimate the whole channel, including the channel between the base station (BS) and the RIS, that between the users and the RIS, and that between the BS and the users. The whole channel is acquired at the hybrid RIS through the transmission of several segments of training pilots. In order to decrease the hardware cost, the BS and the hybrid RIS are equipped with RF chains with low-resolution analog-to-digital converters (ADCs). Since the numbers of BS antennas and RIS elements are very large, the estimation of the full-space channels is not straightforward. To tackle this problem, we propose a channel extrapolation scheme based on a joint selection model. Specifically, we select a BS antenna subset and an RIS element subset to be connected to the RF chains and to estimate the partial-space channels related to these subsets. Then, a reference-based variational auto-encoder model is used to implement the extrapolation from the partial-space channels to the full-space channels. Besides, the optimal joint selection pattern is acquired through a selection network to improve the channel extrapolation performance. Moreover, to overcome the quantization error caused by the use of low-resolution ADCs, we propose a two-stage repair scheme for channel estimation. Simulation results are provided to demonstrate the effectiveness of the designed channel extrapolation scheme.

Orthogonal frequency division multiplexing (OFDM) has been widely used in communication systems operating in the millimeter wave (mmWave) band to combat frequency-selective fading and achieve multi-Gbps transmissions, such as IEEE 802.15.3c and IEEE 802.11ad. For mmWave systems with ultra high sampling rate requirements, the use of low-resolution analog-to-digital converters (ADCs) (i.e., 1-3 bits) ensures an acceptable level of power consumption and system costs. However, orthogonality among sub-channels in the OFDM system cannot be maintained because of the severe non-linearity caused by low-resolution ADC, which renders the design of data detector challenging. In this study, we develop an efficient algorithm for optimal data detection in the mmWave OFDM system with low-resolution ADCs. The analytical performance of the proposed detector is derived and verified to achieve the fundamental limit of the Bayesian optimal design. On the basis of the derived analytical expression, we further propose a power allocation (PA) scheme that seeks to minimize the average symbol error rate. In addition to the optimal data detector, we also develop a feasible channel estimation method, which can provide high-quality channel state information without significant pilot overhead. Simulation results confirm the accuracy of our analysis and illustrate that the performance of the proposed detector in conjunction with the proposed PA scheme is close to the optimal performance of the OFDM system with infinite-resolution ADC.

In this paper, we present a new Doppler spread estimation algorithm for broadband wireless orthogonal frequency division multiplexing (OFDM) systems with fast time-varying and frequency-selective Rayleigh or Rician fading channels. The new algorithm is developed by analyzing the statistical properties of the power of the received OFDM signal in the time domain, thus it is not affected by the influence of frequency-domain inter-carrier interference (ICI) introduced by channel variation within one OFDM symbol. The operation of the algorithm doesn’t require the knowledge of fading channel coefficients, transmitted data, or signal-to-noise ratio (SNR) at the receiver. It is robust against additive noise, and can provide accurate Doppler spread estimation with SNR as low as 0 dB. Moreover, unlike existing algorithms, the proposed algorithm takes into account the inter-tap correlation of the discrete-time channel representation, as is the case in practical systems. Simulation results demonstrate that this new algorithm can accurately estimate a wide range of Doppler spread with low estimation latency and high computational efficiency.

Orthogonal frequency division multiplexing (OFDM) has been widely regarded as an effective modulation technique for mitigating the effects of ISI in a frequency selective fading channel and for providing reliable high data rate transmission over wireless links. Adaptive antenna arrays at the base and mobile stations can achieve further increases in system's capacity and bandwidth efficiency, as well as in QoS improvement in conventional OFDM systems. The conventional adaptive antenna arrays based OFDM systems always use the sub-carriers characterized by the first largest eigenvalues to transmit the OFDM block symbols. In this paper and in contrast to previous work, we propose dynamic sub-channel allocation with adaptive beamforming for broadband OFDM wireless transmission systems. The proposed system adaptively selects the eigenvectors associated with the relatively large sub-channel eigenvalues to generate the beamforming weights at the mobile and base stations and then dynamically assigns the corresponding best sub-channels to transmit the OFDM block symbols. It is shown by simulation that, without adding much complexity, the proposed system can achieve a better performance than an adaptive antenna arrays based OFDM system without dynamic sub-channel allocation over multipath fading channels. Simulation results also reveal that the proposed system is not too sensitive to channel estimation errors.

This work investigates the theoretical bounds of the joint localization and synchronization processes in a reconfigurable intelligent surface (RIS)-assisted system. We address the case of millimeter-wave (mm-Wave) multiple-input single-output (MISO) orthogonal frequency-division multiplexing (OFDM) with non-ideal transceivers. Considering a single antenna mobile station MS aims to estimate the parameters of the downlinks from the base station (BS) and the RIS by observing a known sequence received by the MS directly from the BS and indirectly through the RIS. The theoretical bounds of the estimation process are assessed by using the Fisher information matrix (FIM). A transformation matrix is then used to convert the FIM of the downlink channel parameters to the FIM of the MS joint localization and synchronization parameters. Specifically, the transformation matrix is derived based on the geometric relationships that convert the estimated downlink channels’ parameters to the position coordinates and clock offset. Next, the Cramer-Rao lower bound (CRLB) matrix of the joint localization and synchronization process is obtained by using the pseudo-inverse of the FIM. Thus, the position error bound (PEB), as well as the synchronization error bound (SEB), are calculated. Computer simulation results are provided to illustrate the adverse effects of the HWIs on the accuracy of localization and synchronization. These results are given in proportion to the effective signal-to-noise ratio (SNR), the number of pilot transmissions, and the number of the RIS elements.

Massive multiple-input multiple-output (MIMO) systems have attracted much attention lately due to the many advantages they provide over single-antenna systems. Owing to the many antennas, low-cost implementation and low power consumption per antenna are desired. To that end, massive MIMO structures with low-resolution analog-to-digital converters (ADC) have been investigated in many studies. However, the effect of a strong interferer in the adjacent band on quantized massive MIMO systems have not been examined yet. In this study, we analyze the performance of uplink massive MIMO with low-resolution ADCs under frequency selective fading with orthogonal frequency division multiplexing (OFDM) in the perfect and imperfect receiver channel state information cases. We derive analytical expressions for the bit error rate and ergodic capacity. We show that the interfering band can be suppressed by increasing the number of antennas or the oversampling rate when a zero-forcing receiver is employed.

This paper considers a reconfigurable intelligent surface (RIS)-assisted multi-user secrecy transmission in the presence of low-resolution digital-to-analog converters (DACs) at a small-cell base station (SBS). The weighted sum secrecy rate (WSSR) is maximized by jointly designing the active beamforming and RIS reflecting phase shift subject to the transmit power and the phase unit-modulus constraints. However, the problem involves two sum-of-logarithms and highly coupled optimization variables. To tackle the non-convex fractional programming problem with multiple ratios, we employ a lower linearization approach for logarithm subtraction and decompose the problem into two quadratically constrained quadratic programming sub-problems. The optimum active beamforming is determined using a semi-definite relaxation method, and the a closed-form solution of RIS phase shift matrix is derived through the alternating direction method of multiplier. Moreover, considering practical finite-capacity backhaul link, we develop the user scheduling strategy using the power of transmit beamforming as a discrete indicator and formulate the user scheduling as a mixed-integer constraint. The joint optimization of user scheduling and WSSR is investigated by maximizing the network utility with a ‘1-norm constraint. Simulation results demonstrate the effectiveness of the proposed algorithm in achieving significant WSSR performance even in the presence of low-resolution DACs. Furthermore, these results show that the joint optimization of WSSR and user scheduling can maximize the network utility by selecting the activated subset of served users.

Reconfigurable intelligent surface (RIS)-aided communication has been regarded as one of the promising technologies for future wireless networks with regards to controlling the propagation environment and enhancing the quality of the end-to-end communication links. In this study, considering the importance of index modulation (IM) and RIS-aided schemes in 6G networks, first, an RIS-aided orthogonal frequency division multiplexing (OFDM)-IM system design is proposed. Previous studies focusing on RIS-aided OFDM systems are based on an ideal reflection model, where the constant amplitude and variable phase shift of the RIS are independent of the frequency of the incoming signal. However, in realistic applications, this ideal RIS model may not be accurate since both the phase shift and amplitude of RIS elements depend on the frequency, which makes their effect significant, especially for wideband systems. Therefore, this study primarily considers a practical RIS model through designing the RIS reflection coefficients for OFDM-IM systems. In order to further enhance the bit error rate (BER) performance of the RIS-aided OFDM-IM system, an exhaustive search-based optimization algorithm that maximizes the average minimum Euclidean distance (AMED) within the subblocks is also proposed. Moreover, extensive computer simulation results are produced in order to illustrate the performance improvement of the proposed algorithm over the reference algorithms in the literature. The proposed AMED-based reflection coefficient design algorithm provides better BER performance for RIS-aided OFDM-IM systems concerning the presented algorithms.

Reconfigurable intelligent surfaces (RISs) have recently emerged as an innovative technology for improving the energy and/or spectrum efficiency of future wireless communications. In this paper, we propose a transmission protocol for the wideband RIS-assisted single-input multiple-output (SIMO) orthogonal frequency division multiplexing (OFDM) system to execute channel estimation and passive beamforming simultaneously. A new channel estimation method is proposed to progressively resolve the channel state information (CSI) over the training symbols, based on which the passive beamforming at the RIS is optimized to improve the channel gains on the data tones in the remaining training symbols. Based on the incomplete CSI, we formulate an optimization problem to maximize the average achievable rate by designing the passive beamforming at the RIS, which needs to balance the received signal power over different subcarriers and different receive antennas. Moreover, we propose a low-complexity algorithm to find a high-quality solution for the formulated problem. Simulation results validate the effectiveness of the proposed channel estimation and beamforming optimization methods.

Energy efficiency (EE) has become a key performance indicator in designing future wireless networks. In this regard, we propose a novel two reconfigurable intelligent surfaces (RISs) assisted coordinated multipoint (CoMP) network, where two RISs cooperate to reduce energy consumption by constructing an intelligent radio environment. Aiming to maximize this system’s energy efficiency (EE), the joint optimization problem on the cooperative beamforming among base stations (BSs) and passive beamforming among RISs, subject to each user’s data rate requirement, is formulated. An alternative optimization algorithm is proposed by decoupling it into a cooperative beamforming subproblem among BSs and a cooperative reflective coefficients design subproblem among RISs. Dinkelbach’s transform and complex fractional programming algorithms are also invoked to transform these two subproblems into convex optimization problems and obtain the optimal solution for each sub-problem. Numerical results validate the proposed algorithm’s feasibility, fast convergence, and flexibility. It also shows that the proposed scheme with cooperative beamforming design for both BSs and RISs outperforms that without RIS and that with randomly initialized RISs.

In this paper, we propose a novel computer vision-based approach to aid reconfigurable intelligent surface (RIS) for dynamic beam tracking and implement the corresponding prototype verification system. A camera is attached at the RIS to obtain the visual information about the surroundings, with which RIS identifies the incident beam direction and the desired reflected beam direction, and then adjusts the reflection coefficients according to the pre-designed codebooks. We build a 20-by-20 RIS running at 5.4 GHz and develop a high-speed control board to ensure the real-time refresh of the reflection coefficients. Meanwhile we implement an independent peer-to-peer communications system to simulate the physical link between the base station and the user equipment. The vision-aided RIS prototype system is tested in two mobile scenarios: RIS works in near-field conditions as a passive array antenna of the base station; RIS works in far-field conditions to assist the communication between the base station and the user equipment. The experimental results show that RIS can quickly adjust the reflection coefficients for dynamic beam tracking with the help of visual information.

With the development of the next generation of mobile networks, new research challenges have emerged, and new technologies have been proposed to address them. On the other hand, reconfigurable intelligent surface (RIS) technology is being investigated for partially controlling wireless channels. RIS is a promising technology for improving signal quality by controlling the scattering of electromagnetic waves in a nearly passive manner. Heterogeneous networks (HetNets) are another promising technology that is designed to meet the capacity requirements of the network. RIS technology can be used to improve system performance in the context of HetNets. This study investigates the applications of reconfigurable intelligent surfaces (RISs) in heterogeneous downlink networks (HetNets). Due to the network densification, the small cell base station (SBS) interferes with the macrocell users (MUEs). In this paper, we utilise RIS to mitigate cross-tier interference in a HetNet via directional beamforming by adjusting the phase shift of the RIS. We consider RIS-assisted heterogeneous networks consisting of multiple SBS nodes and MUEs that utilise both direct paths and reflected paths. Therefore, the aim of this study is to maximise the sum rate of all MUEs by jointly optimising the transmit beamforming of the macrocell base station (MBS) and the phase shift of the RIS. An efficient RIS reflecting coefficient-based optimisation (RCO) is proposed based on a successive convex approximation approach. Simulation results are provided to show the effectiveness of the proposed scheme in terms of its sum rate in comparison with the scheme HetNet without RIS and the scheme HetNet with RIS but with random phase shifts.

In this paper, we propose a location-aware channel estimation based on the atomic norm minimization (ANM) for the reconfigurable intelligent surface (RIS)-aided millimeter-wave multiple-input-multiple-output (MIMO) systems. The beam training overhead at the base station (BS) is reduced by the direct beam steering towards the RIS with the location of the BS and the RIS. The RIS beamwidth adaptation is proposed to reduce the beam training overhead at the RIS, and also it enables accurate channel estimation by ensuring the user equipment receives all the multipath components from the RIS. After the beam training, the cascaded effective channel of the RIS-aided MIMO systems is estimated by ANM. Depending on whether the beam training overhead at the BS or at the RIS is reduced or not, the channel is represented as a linear combination of either 1D atoms, 2D atoms, or 3D atoms, and the ANM is applied to estimate the channel. Simulation results show that the proposed location-aware channel estimation via 2D ANM and 3D ANM achieves superior estimation accuracy to benchmarks.